[Python] How can I compare clusters with different amounts of datapoints using ARI?

I have two KModes clusters, structured as 1D lists, where each index represents a data point, and the value at that index represents the cluster that the data point falls into.

My issue is that I want to compare these two clusters, and I'm using ARI to do so. ARI requires 2 inputs that are the same size. Is there a way for me to compare these two clusters using ARI? I've tried adding dummy values to the smaller list, and that doesn't seem to work. I'm using SkLearn "adjusted_rand_score."

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